440
IEEE SENSORS JOURNAL, VOL. 7, NO. 3, MARCH 2007
On-Chip Capacitance Sensing for Cell Monitoring
Applications
Somashekar Bangalore Prakash, Student Member, IEEE, and Pamela Abshire, Member, IEEE
Abstract—We describe an integrated circuit for sensing the substrate coupling capacitance of anchorage-dependent living cells in
a standard culture environment. Capacitance is measured using
charge redistribution in response to weak, low frequency electric
field excitations. The underlying biophysical phenomenon results
primarily from the insulating nature of the cell structure and the
counterionic polarization in the surrounding aqueous medium.
The measured capacitance depends on a variety of factors related
to the cell, its growth environment and the supporting substrate.
These include membrane integrity, morphology, extracellular
ionic concentration, adhesion strength, and substrate proximity.
The measured capacitance is an indication of both the interaction
between cells and substrate and cell health. The capacitance
sensor uses the principle of charge sharing and translates sensed
capacitance values to output voltages. The sensor chip has been
fabricated in a commercially available 0.5- m, 2-poly 3-metal
CMOS technology. The sensing technique does not require direct
electrical connection to the aqueous culture medium. We report
results from experiments demonstrating on-chip tracking of cell
adhesion as well as long term monitoring of cell viability in vitro.
Index Terms—Bioelectric phenomena, biological cells, biomedical transducers, capacitance measurement, capacitance transducers, CMOS integrated circuits, dielectric measurements,
dielectric polarization, mixed analog-digital integrated circuits.
I. INTRODUCTION
I
NTEGRATED cell sensing using microelectronic biosensors has the potential to enable a variety of applications
in bioengineering, medicine, homeland security, and environmental sciences [1]–[4]. Miniaturized electronic biosensing
techniques have many advantages to offer in comparison to
traditional biochemical detection approaches. First, it is possible for complex measurements to be minimally disruptive in
that the responses of living cells can be monitored in real time
without altering the biochemical composition of the extracellular environment. This prevents unnecessary modification of
the in vitro cellular environment which can interfere with the
analysis procedure and produce unintended side effects. In addition, microfabrication technologies can readily produce sensing
interfaces with physical dimensions matched to the living
samples under study, including single cells or even subcellular
Manuscript received March 14, 2006; revised May 15, 2006; accepted August
3, 2006. This work was supported in part by the National Science Foundation
under Awards 0238061 and 0515873 and by the Laboratory for Physical Sciences. The associate editor coordinating the review of this paper and approving
it for publication was Dr. Jenny Gun.
The authors are with the Integrated Biomorphic Information Systems Laboratory, Institute for Systems Research and Department of Electrical and Computer
Engineering, University of Maryland, College Park, MD 20742 USA (e-mail:
sombp@isr.umd.edu; pabshire@isr.umd.edu).
Digital Object Identifier 10.1109/JSEN.2006.889213
structures [5]. This enables novel measurement methodologies
with capability for exquisite sensitivity and spatial resolution.
Electronic biosensing also offers the flexibility of probing
living samples over time scales varying over many orders of
magnitude and tailored to the specific application. Further,
lab-on-a-chip microsystems may provide versatile solutions to
complex biosensing problems by automating the sensing and
analysis procedures. Such automated, integrated systems offer
the potential to reduce infrastructure and cost requirements and,
ultimately, to make such sophisticated measurements possible
outside the confines of a cell biology laboratory.
The electrical properties of biological cells and tissues have
a strong correlation with their morphological and physiological states [6], [7]. For example, the existence of the membrane
potential is a feature that can be used to distinguish between
living and nonliving cells. In special cell types such as neurons
and muscle cells, the time-varying electrical potential across
the cell membrane reflects changes in the cellular environment
and serves as a mechanism for both intra- and inter-cellular
communication. Impedance measurements can be used to sense
cell morphology and motion [8], to monitor cell adhesion and
growth [9], to measure transepithelial and transendothelial electrical resistances of cultured cell monolayers [10], and also to
differentiate between normal and abnormal cell types [11].
We have developed a CMOS biosensor for characterizing cell
adhesion and monitoring cell viability by sensing the capacitive
coupling between a sensing electrode and the cellular matrix.
The sensing electrode for the biosensor is electrically and biochemically isolated from the cell environment. The technique
does not require direct electrical connection between the cell
culture medium and a reference electrode. The sensor operation also does not rely on any specialized 3-D arrangement of
electrodes. The electrodes are arranged in a planar configuration
within the substrate of the growth chamber and are insulated
from the growth medium. The underlying biophysical phenomenon is that, on exposure to low frequency, low strength electric
fields, living cells in growth medium behave as insulating structures surrounded by ionic clouds compensating fixed charges
present in their membranes [12]. An electric field polarizes the
counterionic cloud, giving rise to electric dipoles which are the
dominant factor responsible for the low frequency capacitive behavior of cells. Healthy cells with well formed plasma membranes sustain stronger electric dipoles than dead or unhealthy
cells with compromised membrane structures, so the measured
capacitance is higher for healthy cells. In addition, healthy cells
adhere more tightly to a surface in comparison with dead or unhealthy cells, which results in stronger capacitive coupling between the cells and underlying electrodes. Both of these properties can be exploited to monitor the health of cells and also their
interaction with substrates.
1530-437X/$25.00 © 2007 IEEE
PRAKASH AND ABSHIRE: ON-CHIP CAPACITANCE SENSING FOR CELL MONITORING APPLICATIONS
Integrated capacitance sensing offers additional advantages
in comparison to other cell sensing modalities such as optical
detection [13], fluorescence sensing [14], and frequency-based
measurements [15]. These include reduced system complexity,
elimination of off-chip optics, no postfabrication requirements,
and prevention of electrochemical side-effects which are prominent in electrode-based sensors with sensing surfaces exposed
directly to the cell medium. On-chip capacitance sensing in
combination with dielectrophoretic actuation has already been
employed for cell detection and manipulation. Romani et al.
developed a CMOS lab-on-a-chip incorporating a capacitance
sensor array and dielectrophoretic cages for localization of
bioparticles, wherein the sensors detect variations in the dielectric permittivity due to the presence of bioparticles in between
the on-chip electrodes and an external conducting lid [16].
We have pursued an alternate approach employing a CMOS
capacitance sensor for sensing variations in capacitive coupling
between the sensing electrode and the cell-medium-substrate
interface, as a means for characterizing cell adhesion and
monitoring cell viability [17], [18].
The remainder of this paper is organized as follows. Section II
reviews the biological basis for cell adhesion and viability characteristics and the traditional methods that are used to quantify
them. Section III gives an overview of the interactions between
cells and substrates, and discusses the biophysical phenomena
underlying the sensing mechanism reported here. Section IV
describes the capacitance sensor design along with the modeling and calibration of capacitance measurements. Section V
presents results from experiments performed in vitro with living
cells cultured directly on the chip surface. Section VI summarizes this paper.
II. CELL ADHESION AND VIABILITY
Interaction with a substrate plays a crucial role in the lifecycle of a majority of cell types. This is because most cells are
anchorage dependent, that is, they need to be attached to a solid
surface before they can grow and proliferate. The mechanisms
by which living cells adhere to substrates and their subsequent
viability have been extensively studied in cell biology. In addition to its physiological significance, understanding cell adhesion has many practical applications in the fields of medicine,
bioengineering, and environmental sciences. For example, the
formation of biofilms (complex aggregations of microorganisms
on solid surfaces) is important in a variety of applications in food
and water quality assessment and treatment [19]. Studying and
enhancing cell adhesion to body implants is extremely important for improving biocompatibility, reliability, lubrication, and
self-regeneration of the adjacent tissues [20].
A. Characterizing Cell Adhesion
Living cells exhibit a variety of modes of attachment to
substrates [21]. Cell adhesion is a complex process that results
from interplay between many molecular and macromolecular
forces including receptor mediated forces, membrane elasticity,
and different kinds of interfacial forces including electrostatic,
undulation, van der Waals interaction, and hydration forces
[22]. The diversity of mechanisms underlying cell adhesion
ultimately enables cells to adapt to different kinds of surfaces
and living conditions. The factors influencing the interactions
441
between cells and their substrates can be characterized by
quantifying cell adhesion.
In this direction, previous efforts employed techniques like
centrifugation and shear flow measurements [23], wherein cells
cultured on a substrate are subjected to centrifugal and flow
forces, respectively. The adhesion strength is related to the
fraction of cells that become detached from the surface during
mechanical manipulation. Such macroscopic measurements on
entire cell populations provides limited information regarding
individual cell behavior and the statistical variations among
cells, and are inherently disruptive of the cell-substrate coupling. Bowen et al. used atomic force microscopy to measure
the adhesive force of a yeast cell by immobilizing it at the
end of a cantilevered beam and making force-distance measurements for cell retraction from the surface [24]. Barbee
et al. developed a thickness shear mode piezoelectric sensor
for continuous measurement of interfacial processes between
endothelial cells and gold electrodes [25]. Fan et al. studied the
adhesion and viability of central neural cells on silicon wafers
with different surface roughness conditions using scanning
electron microscopy [26].
B. Assessing Cell Viability
Quantification of cell viability has become an essential requirement for cell-based studies. Viability sensors may be useful
for optimization of cell culture conditions and also for a variety
of commercial applications such as drug screening and biocompatibility characterization of implants.
Cell viability can be measured either directly by counting
the number of healthy cells in a sample or indirectly by measuring an indicator of cell health and proliferation. Most existing
methods for estimation of cell viability can be classified into two
categories. The first class is based on quantifying the metabolic
activity of cells [27], [28]. This is accomplished by incubating
cells along with an indicator dye or a tetrazolium salt that is reduced to a colored compound only by metabolically active cells.
Color development is a function of the number of metabolically
active cells, and gives a measure of cell viability. Quantification
is normally accomplished using spectrophotometry. The other
class of cell viability methods probe the cell membrane integrity
using dye-exclusion techniques [28]. This approach takes advantage of the fact that healthy cells with well formed plasma
membranes exclude dyes such as trypan blue, whereas dead and
unhealthy cells with compromised membranes allow dyes to
stain internal cellular components. Microscopic analysis is required in order to count only healthy cells and reject unhealthy
cells in the sample.
C. Proposed Approach
All the approaches mentioned before for characterizing cell
adhesion and monitoring cell viability employ specialized techniques and processes. In addition, most of them require sophisticated laboratory equipment. Almost all of these cell viability
methods involve an inherent process of sampling which may
not be feasible for samples with extremely small volumes. The
purpose of this work is to develop an integrated sensor that
can be designed and fabricated using conventional CMOS technology, for inexpensive, portable, and reproducible characterization of cell adhesion and viability properties, without the need
for extensive laboratory infrastructure. The integrated sensing
442
IEEE SENSORS JOURNAL, VOL. 7, NO. 3, MARCH 2007
Fig. 1. Cellular counterionic polarization in the presence of external electric
fields.
approach offers the unique advantage of long term continuous
cell monitoring in a standard in vitro environment without the
need for disruptive external forces or biochemical agents.
III. BIOPHYSICS OF CELL-SUBSTRATE CAPACITANCE
In the presence of low frequency, low strength electric
field excitations, living cells behave as insulating structures
embedded in an electrically conductive growth medium which
is an aqueous ionic solution. Cell surfaces generally carry
a surface charge density, which can be positive or negative
depending upon the cell type [12]. The majority of cell surfaces
are negatively charged. This induces a counterionic cloud
around the cells in the surrounding medium. When exposed
to an external electric field these counterions are displaced
tangentially around the cell surface giving rise to an induced
dipole moment as illustrated in Fig. 1. Both the insulating nature of cells at low excitation frequencies and the counterionic
polarization are responsible for the capacitive behavior of cells.
A. Correlating Capacitance With Cell-Substrate Interaction
Next, we examine the behavior of a cell suspension when it
comes into contact with a solid biocompatible substrate. Upon
contact with a solid substrate, proteins in the growth medium
spontaneously adsorb onto the substrate. The interaction between cells and substrate begins with the sedimentation phase
when the suspended cells gradually drift downwards and settle
on the surface. This is followed by the adhesion phase when
cells anchor themselves to the surface through various mechanisms at both molecular and cellular levels [22]. This is accompanied by a significant change in cell morphology wherein the
cells exhibit a spreading behavior. Under favorable conditions,
there is a proliferation phase during which cells divide and proliferate. In the presence of weak, low frequency electric fields,
all three phases can be modeled as a process of cell dielectric
layer formation as shown in Fig. 2.
The capacitance arising from this dielectric layer successively
increases in the phases described previously. The capacitance
between cells and substrate is lowest in the sedimentation phase
since the cells are far from the surface and the cellular dielectric
layer is not yet completely formed. During the adhesion phase
there is a remarkable decrease in the dielectric layer thickness
due to cell spreading and anchoring mechanisms. In addition,
the effective dielectric constant of the cell layer increases due
to increasing cell membrane surface area and increasing cell
dipole density. Both factors contribute to a steady increase in
the cell dielectric layer capacitance. Once the cells have adhered
to the surface and adjusted to the culture conditions, the proliferation phase begins and the measured capacitance reflects
ongoing cellular activity. In cases of adverse conditions, the
Fig. 2. Cell dielectric layer formation in the presence of weak, low-frequency
electric fields: sedimentation phase (top, middle), adhesion, and proliferation
phases (bottom) [18].
growth phases described previously may be superseded by a cell
death phase during which the plasma membranes begin to disintegrate, causing a reduction in capacitance of the cell dielectric
layer.
IV. CELL-SUBSTRATE CAPACITANCE SENSING
Integrated capacitance sensors have been employed for a variety of applications including fingerprint sensing [29], position sensing [30], interconnect characterization [31], humidity
sensing [32], and particle detection [33]. We report an adaptation of this technique for tracking cell adhesion and monitoring
viability.
A. Sensor Design and Operation
A custom CMOS capacitance sensor for cell sensing has been
designed using the topology shown in Fig. 3 [18], [34]. The
sensor operation is based upon the charge sharing principle. The
and
sensor circuit has two nodal parasitic capacitances
whose charging and discharging are controlled by a set of three
MOSFET switches M1, M2, and M3. The sensor operates in
two phases. In the reset phase, switches M1 and M3 are turned
and node N2 to
, while M2 is
on, charging node N1 to
off. In the evaluation phase, M2 is turned on, while M1 and M3
and
. The
are off, redistributing the charges between
joint nodal voltage
is a function of the sensed capacitance
as a result of the charge redistribution
(1)
Referring back to Fig. 3, the topmost metal layer, metal3,
forms the sensing electrode. Sensitivity of the measurement is
maximized by minimizing the nodal parasitics. For this purpose,
the fringe capacitances between the sensing electrode and the
substrate are shielded by means of a larger area metal2 plate
in the lower layer. The large capacitance between the sensing
electrode and the shield is canceled by driving the metal2 shield
with a potential that tracks the sensing electrode potential using
a unity-gain buffer. Sensor dynamic range improves with increasing sensing electrode area.
PRAKASH AND ABSHIRE: ON-CHIP CAPACITANCE SENSING FOR CELL MONITORING APPLICATIONS
Fig. 3. Cell-substrate capacitance sensor: design and operation [18].
Fig. 4. (Left) photomicrograph of the fabricated sensors. (Right) photograph
of the biocompatibly packaged sensor chip [18].
The circuit has been designed for a supply voltage of 3 V
and has been fabricated in a commercially available 0.5- m
CMOS technology with three metal layers. Three groups of sensors with electrode areas of 20 20 m , 30 30 m and
40 m have been designed and tested. Fig. 4 shows a
40
photomicrograph of the fabricated sensors. The sensor chip has
been used to characterize coupling capacitance between cells
and substrate at a reset frequency of 1 kHz, as described in further detail in Section V.
B. Model of the Sensed Capacitance
Several factors influence the capacitance measured at the
sensing electrode by the circuit. These factors include the
following.
: The passivation
1) Passivation Layer Capacitance
layer of the fabrication process electrically isolates the sensing
electrode from the cell environment. For a passivation layer
with uniform thickness of 1 m and a dielectric constant of 6,
the capacitance per unit area is approximately 0.05 fF/ m .
This capacitance could be increased, and overall sensitivity
enhanced, by thinning the passivation layer over the electrodes.
However, this would require custom process development,
443
raising significant practical issues as well as associated cost,
and would limit the generality of the technique. The chip was
fabricated in a commercially available CMOS technology, so
the sensor design was constrained by the limitations imposed
by the process technology.
: The passivation layer (a
2) Interfacial Capacitance
solid surface) is in direct contact with the cell growth medium
(an aqueous ionic solution), resulting in a layered polarized interface according to Gouy–Chapman–Stern theory [35]. The adhesion process of cells introduces additional solid-liquid interfaces. All these phase separations give rise to interfacial capacitances on the order of 100 fF/ m , 3–4 orders of magnitude
larger than the passivation layer capacitance.
: As discussed in Section II,
3) Cell Layer Capacitance
after sedimentation the cells form a complex dielectric layer at
the growth medium-passivation layer interface. Ionic conductances are neglected in the model since the cell environment is
exposed to weak electric fields with no current flow. Thus, the
cell layer is regarded as purely capacitive. In reality, the cells
form a heterogeneous layer which exhibits both spatial and temporal variation of dielectric properties. Assuming that the dielectric constant of the insulating cell layer depicted in Fig. 2 is
[36] and that the
equal to that of the plasma membrane
thickness of the cell layer is 5–10 m, the cell layer capacitance
is on the order of magnitude of 0.01 fF/ m , comparable with
that of the passivation layer.
: The electric field originating
4) Fringe Capacitance
from the sensing electrode can be resolved into vertical and
lateral components. The vertical component dominates at the
electrode center while the lateral component dominates at the
electrode periphery. The lateral coupling gives rise to fringe
capacitances. The fringe capacitance includes all parasitic
capacitances arising from the lateral coupling of the sensing
electrode with the neighboring metal lines, passivation layer,
cells, and growth medium. The fringe capacitances are on the
order of 10 aF/ m, and therefore, their effect cannot be ignored.
: The baseline capacitance
5) Baseline Capacitance
represents the capacitance due to dielectric properties of
residual materials on top of the passivation layer. These include
surface residues resulting from the polymer used for encapsulation of the bond wires and from adsorption of materials
from the growth medium onto the surface. Experimentally, the
initial capacitance sensed by a 40 40 m sensor was found
to vary between sub-femtofarad values to approximately 10 fF
(for a 30 30 m sensor, between sub-femtofarad values to
20 m sensor, between
approximately 2 fF, and for a 20
sub-femtofarad values to approximately 1 fF). We attribute
these variations in initial sensed capacitances to different
at the start of different experiments.
is
values of
sensitive to a variety of factors including surface residues on
the passivation layer, pH of the growth medium, microscopic
air bubbles, and hydrodynamic disturbances.
From the previous discussion, the capacitance as seen by the
sensing electrode equates to the effective capacitance offered by
the network of passivation layer, cell layer, fringe parasitics, and
all interfacial capacitances between various liquid-solid boundaries. The sensed capacitance must be modeled separately for
the preadhesion and the post-adhesion phases, since during the
444
IEEE SENSORS JOURNAL, VOL. 7, NO. 3, MARCH 2007
capacitance, and effectively limiting the sensed capacitance to
the passivation layer capacitance.
Considering the relative orders of magnitude of the various
capacitances, the effective value of preadhesion sensed capacitance can be modeled as
(2)
The cells do not influence the cell-substrate capacitance until
they have settled on the substrate below the ionic screen, and
are exposed to the varying electric fields. This happens during
the adhesion phase when the cellular dielectric layer begins to
form on the surface of the passivation layer. The interface between the ionic screen and the solid surface becomes permeated
with cellular dipoles enhancing its dielectric constant. The efwith
, as illustrated in
fect is modeled by replacing
is also influenced by the cells
Fig. 5(b). During this process
present in neighboring regions. This effect is incorporated into
with
. The adhesion and post-adthe model by replacing
hesion phase sensed capacitance can be modeled as
(3)
Fig. 5. Models of sensed capacitance during the different phases of the interaction process between cells and substrate. (a) Preadhesion phase model.
(b) Adhesion and post-adhesion phase model.
adhesion phase the interface between the growth medium and
the substrate undergoes a drastic change in its structural and dielectric properties resulting in an appreciable variation in the
sensed capacitance. Both models of sensed capacitance are illustrated in Fig. 5.
During the preadhesion phase of Fig. 5(a), the growth
medium produces an ionic screen in response to the electric
field originating from the sensing electrode. The ionic screen
at the boundary between the growth medium and the substrate
shields the interior of the solution including the suspended cells.
The sensed capacitance network comprises the passivation layer
and interfacial capacitances
in series with
capacitance
. The fringe capacitance
the baseline capacitance
appears in parallel with
[see Fig. 5(a)]. The reference
potential for the fringe capacitance originates from adjacent
metal interconnects resting at dc potentials. The reference
potential for the capacitances associated with vertical electric
field coupling originates from the growth medium, although
there is no need for direct electrical connection between the
growth medium and the circuit. Under equilibrium conditions
the bulk of the growth medium is electrically neutral and is free
of potential gradients. Introduction of a ground electrode in
the growth medium has been observed to shield out the sensed
capacitance network and saturate the sensors. The grounded
medium behaves as an ionic conductor in contact with the
passivation layer, screening most components of the vertical
It is important to note that
,
,
, and
represent lumped parameter values of their corresponding capacitances which are actually distributed in nature due to their heterogenous and time-varying characteristics. As mentioned preis a function of many
viously, the cell layer capacitance
factors influencing its structural and dielectric properties [6],
[7], [37]. These include membrane integrity, membrane potential, cell morphology, adhesion strength, extra-cellular ionic distributions, and also number and surface area coverage of cells
above the sensing electrode.
C. Sensed Capacitance Computation
The transducer was calibrated as a proximity detector by
using an external metal electrode whose vertical positioning
was controlled by means of a piezoelectric micropositioner.
Based upon bench test results the nodal parasitic capacitances
and
were estimated using least squares fits to be 20
and 18 fF, respectively [17]. In order to translate the sensor
outputs to sensed capacitance values, the output voltages during
the evaluation phase are subtracted from their corresponding
voltages during the reset phase for offset cancellation. In some
cases, this results in negative values of sensed capacitances due
to small voltage fluctuations. The inverse relation for
as
a function of this voltage difference can be derived from (1) as
(4)
where
and
and
. Here, both
refer to the voltages before the readout buffer.
V. SENSOR RESPONSE TO LIVING CELLS
For the purpose of in vitro testing, the sensor chip in a 40-pin
DIP ceramic package was encapsulated using a biocompatible
polymer for bond wire insulation and isolation of cells from
PRAKASH AND ABSHIRE: ON-CHIP CAPACITANCE SENSING FOR CELL MONITORING APPLICATIONS
445
toxic materials of the chip package. The encapsulation material is a low water absorbing photopatternable polymer [38]. A
well was formed on top of the chip surface for containing the
cell culture. Fig. 4 shows a photograph of the final assembly.
All experiments were conducted with fresh unused chips possessing clean surfaces without any additional surface modification or functionalization. The capacitance measurements were
performed without grounding the culture medium.
A. Tracking Cell Adhesion
In this experiment, the sensor chip was tested with bovine
aortic smooth muscle cells (BAOSMC). These cells were cultured in a commercially prepared medium supplemented with
serum, growth factors, and antibiotics (Cell Applications Inc.).
A data acquisition system was set up for online monitoring of
the sensor responses to BAOSMC loaded on top of the chip
surface and placed inside an incubator. The sensor chip was
rinsed with deionized water, sterilized using ultraviolet radiation and then rinsed with BAOSMC growth medium, before
cells were loaded into the culture well. BAOSMC loading and
incubation were performed using standard aseptic techniques.
The test fixture containing the sensor chip was maintained at
37 C, 5% CO inside an incubator during the monitoring period. The sensor readings were recorded every 5 min with the
cells exposed to electric field excitations only during the short
recording intervals.
Fig. 6 shows the sensed capacitances as recorded concurrently by six 40 40 m sensors during the first 8 h of cell incubation. The capacitance plots clearly illustrate the sedimentation
and adhesion phases as discussed in Section III. The cells took
around 2.0–4.75 h to sediment and around 30 min to 1.5 h to adhere (sedimentation: 3.29 1.05 h, adhesion: 1.08 0.34 h). The
figure also shows phase delays in the initiation of cell adhesion
as recorded by sensors in different locations. Identical experiments were conducted with breast cancer cells (MDA-MB-231)
which demonstrate similar sensor responses to cell adhesion.
B. Monitoring Cell Viability
In this experiment, the sensor responses were continuously
acquired every 5 min for a period of 29 h with BAOSMC incubated on top of the chip surface. For validation purposes, cell
viability was confirmed using Alamar blue (obtained in aqueous
form from Biosource International), a cell viability dye. Alamar
blue is commercially available in an oxidized, blue, nonfluorescent form (resazurin), which becomes gradually reduced to its
pink fluorescent form (resorufin) in a medium containing viable
cells [28]. The dye molecules are reduced by a class of enzymes
called reductases found in mitochondrial membranes and the cytosol [39]. Reduction of Alamar blue is directly correlated with
the number of viable cells, incubation time, and temperature.
The resazurin reduction test has increasingly been used in cytotoxicity assays for high-throughput screening in pharmacological applications [40] because it is nontoxic and nonterminal,
that is, it does not require that the cells in the sample be killed
in order to make the measurement.
BAOSMC loading and incubation were performed as in the
previous experiment, with Alamar blue mixed into the growth
medium in a 1:10 ratio by volume. The culture well has a sample
Fig. 6. Online tracking of cell adhesion process by six 40
2 40 m
sensors.
capacity of approximately 500 L. Fig. 7 shows the sensed capacitances as recorded concurrently by three of the on-chip sensors, one representative trace from each sensor group with different sensing electrode area. The encapsulated chip package
functioned during an incubation period of 29 h, after which the
encapsulation material failed due to water absorption. The fraction of Alamar blue in reduced form was evaluated by measuring
the absorbance of the growth medium at 570 and 600 nm. This
was accomplished by performing spectrophotometric analysis
on 20 L samples extracted from the sensor well at instances
during the monitoring period denoted by the vertical time lines
in Fig. 7.
The sensed capacitance values tracked the initial sedimentation and adhesion phases as in the previous experiment. After
adhesion the sensed capacitances remained high until the ninth
hour of incubation, which is indicative of viability. Alamar blue
was gradually reduced to its pink form during this 9-h interval,
confirming positive cell viability. According to spectrophotometric readings, the fraction of Alamar blue in reduced form
was found to be 0%, 58.5%, and 73.8% at 0, 4, and 9 h, respectively, with reference to the initial cell loading time. Over
the next 15 h, however, the sensed capacitances began to fall
gradually, which is indicative of compromised viability. This
decrease is attributed to oxygen deprivation resulting from the
presence of a gas impermeable glass cover slip over the sensor
well. The cover slip served to maintain sterility of the sample
well during the extended observation period. In order to confirm the observed reduction in cell viability, the sensor well was
replenished at the beginning of the second day with a fresh solution of growth medium and Alamar blue. As seen in Fig. 7, over
the next 1 h interval the capacitances increased and stabilized,
possibly due to the fresh oxygen and nutrient supply. However,
over the next few hours the capacitances decreased again, which
is indicative of compromised viability. This result is confirmed
by the concurrent Alamar blue measurements: minimal color
change was observed, in contrast to measurements of the previous day. Alamar blue % reduction values were found to be
0%, 0.95%, and 7.15% at 0, 4, and 8 h, respectively, with reference to the growth medium replenishment time on the second
day. The transient drops in the sensed capacitance values at the
microsample extraction times can be attributed to hydrodynamic
446
IEEE SENSORS JOURNAL, VOL. 7, NO. 3, MARCH 2007
Fig. 7. Online monitoring of cell viability with concurrent measurements using Alamar blue dye. Alamar blue percent reduction values obtained from spectrophotometric analysis are shown above the times corresponding to extraction of the microsample.
TABLE I
STANDARD DEVIATIONS OF CAPACITANCE FLUCTUATIONS
disturbances created by introducing the micropipette tip inside
the culture well. Hydrodynamic effects have the potential to disturb the ionic equilibrium responsible for the biophysical origin
of the cell-substrate capacitance.
In this experiment, good correlation was observed between
on-chip measurements of the capacitance between cells and substrate, and the Alamar blue reduction measurements of cellular
metabolism. An analogous correlation between the sensed capacitance variations and the retention of neutral red dye was
previously reported in [18].
VI. CONCLUSION
A CMOS capacitance sensor chip has been designed to measure the capacitance between cells and substrate, an indicator of
cell adhesion and viability. Biophysical factors contributing to
the sensed capacitance variations were identified and discussed.
Three groups of sensors with electrodes of different sizes were
bench tested for calibration of the relationship between capacitance and measured voltage. In vitro test results with BAOSMC
show that the sensors are able to detect variations of the cell-substrate capacitance in the fF range, with different sensing ranges
for the three sensor groups. Online monitoring results show that
the sensors are effective in tracking different phases of the interaction between cells and substrate. Good correlation was observed between on-chip measurements of cell-substrate capacitance and concurrent Alamar blue dye reduction measurements.
The integrated sensing of capacitance between cells and
substrate offers an important monitoring capability for the
development of cell-based lab-on-a-chip technologies. This
sensor can serve as a useful tool for a variety of cell monitoring
applications including biocompatibility characterization, drug
screening, and medical diagnosis.
C. Capacitance Fluctuations
In both experiments, the sensed capacitances exhibit nonperiodic fluctuations before and after the adhesion phase (see Figs. 6
and 7). These fluctuations were evaluated under different conditions for the three sensor groups; Table I summarizes the standard deviations ( ,
, and
). The fluctuations in response
to cells after adhesion are 1–2 orders of magnitude higher than
when the sensors were exposed to just growth medium or air.
Such fluctuations are consistently observed in the presence of
cells. This can be attributed to increased capacitive crosstalk between the metal interconnects and the sensing nodes, due to increased dielectric constant of the passivation layer surface after
cell adhesion.
ACKNOWLEDGMENT
The authors would like to thank the MOSIS service for providing chip fabrication; these chips are being used to teach an
undergraduate course in mixed signal VLSI design. They also
thank M. Urdaneta and Dr. E. Smela for their technical assistance with the biocompatible chip package. They also thank N.
M. Nelson, Dr. A. Nan, and Dr. H. Ghandehari for their technical assistance with cell culture.
REFERENCES
[1] G. T. A. Kovacs, “Electronic sensors with living cellular components,”
Proc. IEEE, vol. 91, no. 6, pp. 915–929, Jun. 2003.
PRAKASH AND ABSHIRE: ON-CHIP CAPACITANCE SENSING FOR CELL MONITORING APPLICATIONS
[2] D. S. Gray, J. L. Tan, J. Voldman, and C. S. Chen, “Dielectrophoretic
registration of living cells to a microelectrode array,” Biosen. Bioelectron., vol. 19, pp. 1765–1774, 2004.
[3] B. H. Weigl, R. L. Bardell, and C. R. Cabrera, “Lab-on-a-chip for drug
development,” Adv. Drug Delivery Rev., vol. 55, pp. 349–377, 2003.
[4] R. Khamsi, “Labs on a chip: Meet the stripped down rat,” Nature, vol.
435, pp. 12–13, 2005.
[5] M. Abonnenc, L. Altomare, M. Baruffa, V. Ferrarini, R. Guerrieri,
B. Iafelice, A. Leonardi, N. Manaresi, G. Medoro, A. Romani, M.
Tartagni, and P. Vulto, “Teaching cells to dance: The impact of
transistor miniaturization on the manipulation of populations of living
cells,” Solid-State Electron., vol. 49, pp. 674–683, 2005.
[6] K. R. Foster and H. P. Schwan, “Dielectric properties of tissues and
biological materials: A critical review,” Crit. Rev. Biomed. Eng., vol.
17, pp. 25–104, 1989.
[7] E. Gheorghiu, “Measuring living cells using dielectric spectroscopy,”
Bioelectrochem. Bioenergetics, vol. 40, pp. 133–139, 1996.
[8] I. Giaever and C. R. Keese, “A morphological biosensor for mammalian cells,” Nature, vol. 366, pp. 591–592, 1993.
[9] R. Ehret, W. Baumann, M. Brischwein, A. Schwinde, and B. Wolf,
“On-line control of cellular adhesion with impedance measurements
using interdigitated electrode structures,” Med. Biol. Eng. Comput., vol.
36, pp. 365–370, 1998.
[10] J. Wegener, M. Sieber, and H.-J. Galla, “Impedance analysis of epithelial and endothelial cell monolayers cultured on gold surfaces,” J.
Biochem. Biophys. Methods, vol. 32, pp. 151–170, 1996.
[11] Y. C. Lin, M. Li, C.-Y. Wu, W. C. Hsiao, and Y. C. Chung, “Microchips
for cell-type identification,” TAS, pp. 933–937, 2003.
[12] C. L. Davey and D. B. Kell, “The low-frequency dielectric properties
of biological cells,” in Bioelectrochemistry: Principles and Practice,
Vol. 2, Bioelectrochemistry of Cells and Tissues, D. Walz, H. Berg, and
G. Milazzo, Eds. Cambridge, MA: Birkhauser, 1995.
[13] N. Manaresi, A. Romani, G. Medoro, L. Altomare, A. Leonardi, M.
Tartagni, and R. Guerrieri, “A CMOS chip for individual cell manipulation and detection,” IEEE J. Solid-State Circuits, vol. 38, no. 12, pp.
2297–2305, Dec. 2003.
[14] P. N. Zeller, G. Voirin, and R. E. Kunz, “Single-pad scheme for integrated optical fluorescence sensing,” Biosen. Bioelectron., vol. 15, pp.
591–595, 2000.
[15] X. Huang, D. W. Greve, D. D. Nguyen, and M. M. Domach,
“Impedance based biosensor array for monitoring mammalian cell
behavior,” in Proc. IEEE Sensors, 2003, pp. 304–309.
[16] A. Romani, N. Manaresi, L. Marzocchi, G. Medoro, A. Leonardi, L.
Altomare, M. Tartagni, and R. Guerrieri, “Capacitive sensor array for
localization of bioparticles in CMOS lab-on-a-chip,” in Dig. Techn. Papers IEEE ISSCC, 2004, pp. 224–225.
[17] S. B. Prakash, M. Urdaneta, E. Smela, and P. Abshire, “A CMOS
capacitance sensor for cell adhesion characterization,” in Proc. IEEE
ISCAS, 2005, pp. 3495–3498.
[18] S. B. Prakash and P. Abshire, “A CMOS capacitance sensor that monitors cell viability,” in Proc. IEEE Sensors, 2005, pp. 1177–1180.
[19] I. S. Kim, A. Jang, V. Ivanov, O. Stanikova, and M. Ulanov, “Denitrification of drinking water using biofilms formed by Paracoccus denitrificans and microbial adhesion,” Environment. Eng. Sci., vol. 21, pp.
283–290, 2004.
[20] B. Shi, A. Fairchild, Z. Kleine, T. Kuhn, and H. Liang, “Effects of surface texturing on cell adhesion for artificial joints,” Biological Bioinspired Mater. Devices, vol. 823, pp. 139–144, 2004.
[21] R. C. W. Berkeley, J. M. Lynch, J. Melling, P. Rutter, and B. Vincent,
Microbial Adhesion to Surfaces, E. Horwood, Ed. London, U.K.:
Ellis Horwood Ltd., 1980.
[22] A. Baszkin and W. Norde, Physical Chemistry of Biological Interfaces. New York: Marcel Dekker, 2000.
[23] R. J. Doyle, “Strategies in experimental microbial adhesion research,”
in Microbial Cell Surface Analysis. New York: Wiley, 1991.
[24] W. R. Bowen, N. Hilal, R. W. Lovitt, and C. J. Wright, “Direct measurement of the force of adhesion of a single biological cell using an
atomic force microscope,” Colloids Surfaces A: Physicochem. Eng. Aspects, vol. 136, pp. 231–234, 1998.
[25] K. Barbee, S. Kwoun, R. M. Lec, and J. Sorial, “The study of a cellbased TSM piezoelectric sensor,” in Proc. Ann. IEEE Int. Frequency
Control Symp., 2002, pp. 260–267.
[26] Y. W. Fan, F. Z. Cui, L. N. Chen, Y. Zhai, Q. Y. Xu, and I.-S. Lee,
“Adhesion of neural cells on silicon wafer with nanotopographic surface,” Appl. Surface Sci., pp. 313–318, 2002.
447
[27] A. Rollan, D. McCormack, H. McCormack, L. McHale, and A. P.
McHale, “A rapid in-situ, colorimetric assay for the determination of
mammalian-cell viability in alginate-immobilized and encapsulated
systems,” Bioprocess Eng., vol. 15, pp. 47–49, 1996.
[28] A. Schreer, C. Tinson, J. P. Sherry, and K. Schirmer, “Application of
Alamar blue/5-carboxylfluorescein diacetate acetoxymethyl ester as a
non-invasive cell viability assay in primary hepatocytes from rainbow
trout,” J. Analytical Biochem., vol. 344, pp. 76–85, 2005.
[29] S. Shigematsu, H. Morimura, Y. Tanabe, T. Adachi, and K. Machida,
“Single-chip fingerprint sensor and identifier,” IEEE J. Solid-State Circuits, vol. 34, no. 12, pp. 1852–1859, Dec. 1999.
[30] H. U. Meyer, “An integrated capacitive position sensor,” IEEE Trans.
Instrument. Meas., vol. 45, no. 2, pp. 521–525, Apr. 1996.
[31] J. C. Chen, D. Sylvester, and H. Chenming, “An on-chip, interconnect
capacitance characterization method with sub-femto-farad resolution,”
IEEE Trans. Semicond. Manuf., vol. 11, no. 2, pp. 204–210, May 1998.
[32] S. V. Silverthorne, C. W. Watson, and R. D. Baxter, “Characterization
of a humidity sensor that incorporates a CMOS capacitance measurement circuit,” Sensors Actuators, vol. 19, pp. 371–383, 1989.
[33] I. G. Evans and T. A. York, “Microelectronic capacitance transducer
for particle detection,” IEEE Sensors J., vol. 4, no. 3, pp. 364–372, Jun.
2004.
[34] J.-W. Lee, D.-J. Min, J. Kim, and W. Kim, “600-dpi Capacitive fingerprint sensor chip and image-synthesis technique,” IEEE J. Solid-State
Circuits, vol. 34, no. 4, pp. 469–475, Apr. 1999.
[35] W. M. Siu and R. S. C. Cobbold, “Basic properties of the elecsystem: Physical and theoretical aspects,” IEEE
trolyteTrans. Electron Devices, vol. 26, no. 11, pp. 1805–1815, Nov. 1979.
[36] J. Gimsa and D. Wachner, “A unified resistor-capacitor model for
impedance, dielectrophoresis, electrorotation, and induced transmembrane potential,” Biophys J., vol. 75, pp. 1107–1116, 1998.
[37] I. Ermolina, Y. Polevaya, Y. Feldman, B.-Z. Ginzburg, and M.
Schlesinger, “Study of normal and malignant white blood cells by
time domain dielectric spectroscopy,” IEEE Trans. Dielectr. Electr.
Insul., vol. 8, no. 2, pp. 253–261, Apr. 2001.
[38] R. Delille, M. Urdaneta, S. Moseley, and E. Smela, “Benchtop polymer
MEMS,” J. Microelectromech. Syst., vol. 15, no. 5, pp. 1108–1120, Oct.
2006.
[39] R. J. Gonzalez and J. B. Tarloff, “Evaluation of hepatic subcellular fractions for Alamar blue and MTT reductase activity,” Toxicol. In Vitro,
vol. 15, pp. 257–259, 2001.
[40] M. K. McMillian, L. Li, J. B. Parker, L. Patel, Z. Zhong, J. W. Gunnett, W. J. Powers, and M. D. Johnson, “An improved resazurin-based
cytotoxicity assay for hepatic cells,” Cell Biol. Toxicol., vol. 18, pp.
157–173, 2002.
SiO 0 Si
Somashekar Bangalore Prakash (S’06) received
the B.E. (with honors) degree in electrical and
electronics engineering from the Birla Institute of
Technology and Science, Pilani, India, in 2002,
and the M.S. degree in electrical engineering from
the University of Maryland, College Park, in 2004,
where he is currently pursuing the Ph.D. degree in
electrical engineering.
He is currently a Graduate Research Assistant in
the Integrated Biomorphic Information Systems Laboratory, Institute for Systems Research, University of
Maryland. His research interests include mixed-signal integrated circuit design,
CMOS biosensors, and CMOS/MEMS integration targeted towards lab-on-achip technologies.
Pamela Abshire (S’98–M’02) received the B.S.
degree in physics (with honors) from the California
Institute of Technology, Pasadena, in 1992, and the
M.S. and Ph.D. degrees in electrical and computer
engineering from The Johns Hopkins University,
Baltimore, MD, in 1997 and 2002, respectively.
Between 1992 and 1995, she worked as a Research
Engineer in the Bradycardia Research Department of
Medtronic, Inc., Minneapolis, MN. She is currently
an Assistant Professor in the Department of Electrical
and Computer Engineering and the Institute for Systems Research, University of Maryland, College Park. Her research interests
include low-power mixed-signal integrated circuit design, adaptive integrated
circuits, integrated circuits for biosensing, and understanding the tradeoffs between performance and energy in natural and engineered systems.